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Familial tooth agenesis (FTA), distinguished by developmental failure of selected teeth, is one of the most prevalent craniofacial anomalies in humans. Mutations in genes involved in WNT/β-catenin signaling, including AXIN2 WNT10A, WNT10B, LRP6, and KREMEN1, are known to cause FTA. However, mutational interactions among these genes have not been fully explored. In this study, we characterized four FTA kindreds with LRP6 pathogenic mutations: p.(Gln1252*), p.(Met168Arg), p.(Ala754Pro), and p.(Asn1075Ser). The three missense mutations were predicted to cause structural destabilization of the LRP6 protein. Two probands carrying both an LRP6 mutant allele and a WNT10A variant exhibited more severe phenotypes, suggesting mutational synergism or digenic inheritance. Biallelic LRP6 mutations in a patient with many missing teeth further supported the dose-dependence of LRP6-associated FTA. Analysis of 21 FTA cases with 15 different LRP6 loss-of-function mutations revealed high heterogeneity of disease severity and a distinctive pattern of missing teeth, with maxillary canines being frequently affected. We hypothesized that various combinations of sequence variants in WNT-related genes can modulate WNT signaling activities during tooth development and cause a wide spectrum of tooth agenesis severity, which highlights the importance of exome/genome analysis for the genetic diagnosis of FTA in this era of precision medicine.

In this work, we target at solving the Bing challenge provided by Microsoft. The task is to design an effective and efficient measurement of query terms in describing the images (image-query pairs) crawled from the web. We observe that the provided image-query pairs (e.g., text-based image retrieval results) are usually related to their surrounding text; however, the relationship between image content seems to be ignored. Hence, we attempt to integrate the visual information for better ranking results. In addition, we found that plenty of query terms are related to people (e.g., celebrity) and user might have similar queries (click logs) in the search engine. Therefore, in this work, we propose a relevance association by investigating the effectiveness of different auxiliary contextual cues (i.e., face, click logs, visual similarity). Experimental results show that the proposed method can have 16% relative improvement compared to the original ranking results. Especially, for people-related queries, we can further have 45.7% relative improvement.

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